Jobs in Hanau, Deutschland

3 months initial contract

• Remote based with 2 days a month travel to Berlin
• Must be able to start in January
• Strong daily/hourly rates available

We are working with a leading Berlin based technology company who looking for a very strong freelance/contract Data Scientist.

• Own data science at the core of business steering: bring together currently isolated ML models into a unified decision layer that drives budget allocation and conversion optimization—delivering measurable, multi-million-euro impact on the bottom line.
• Build and ship AI agents: design, deploy, and operate production‑grade LLM agents that enhance customer experience across sales and operations, with strong human‑in‑the‑loop controls and continuous improvement.
• Predict and prioritize lead quality: develop and calibrate models that combine likelihood‑to‑book with expected order value to inform lead routing, prioritization, and decision thresholds across the funnel.
• Run deep conversion and funnel analyses: quantify what truly drives conversion, disentangling marketing effects from operational performance using rigorous statistical and causal methods.
• Ensure model reliability and stability: deliver well‑documented, production‑ready models with calibration, drift and anomaly detection, and change controls that protect core business metrics.
• Own broadly and move fast: take end‑to‑end ownership across a wide range of modeling approaches and use cases, prioritizing speed, impact, and pragmatic decision‑making.

• Strong statistical foundation: deep knowledge of statistics, including ensemble methods, linear and logistic models, time‑series and seasonality, and causal inference.
• Advanced experimentation skills: experience designing and analyzing online experiments beyond basic A/B tests—sequential testing, variance reduction, guardrails, and robust metric design.
• Applied agentic AI experience: hands‑on experience building LLM‑based systems (e.g., RAG pipelines, agent workflows) and integrating them into production environments with monitoring and iteration; proficiency in building and maintaining modeling pipelines using tools like pandas, scikit‑learn, and statsmodels, with clean, testable code and monitoring for calibration and drift.
• Solid SQL knowledge: comfortable writing SQL to extract, join, and transform data for analysis and modeling.
• End‑to‑end ownership mindset: proven track record of owning the full lifecycle of DS/ML products—from problem framing and model design through deployment and long‑term monitoring—in real production systems.

• Mid‑Senior level

• Contract

• Information Technology

• Travel Arrangements, Technology, Information and Media, and Data Infrastructure and Analytics

Amsterdam, North Holland, Netherlands